{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "nbsphinx": "hidden"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<style>\n",
       ".output_png {\n",
       "    display: table-cell;\n",
       "    text-align: center;\n",
       "    vertical-align: middle;\n",
       "}\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This is a hidden cell which will be executed but will not show up in Sphinx docs.\n",
    "# To hide a cell, in Jupyter go to Menu->View->Cell Toolbar->Edit Metadata\n",
    "# and enter in {\"nbsphinx\": \"hidden\"}\n",
    "\n",
    "# Set figure size and font size\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['figure.figsize'] = [8, 4]\n",
    "plt.rcParams['font.size'] = 12"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Title for table-of-contents here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's text describing the example.  Here's a literal `Device` and other stuff like *italic* and **bold**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import phidl.geometry as pg\n",
    "from phidl import quickplot as qp\n",
    "from phidl import Device, Group\n",
    "\n",
    "# Create a blank Device\n",
    "D = Device()\n",
    "D << pg.rectangle()\n",
    "\n",
    "# quickplot it!\n",
    "qp(D)\n"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Edit Metadata",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
